The origin of abundance gradients in the Milky Way: the predictions of different models

Aims. We aim to study the abundance gradients along the Galactic disk and their dependence upon several parameters: a threshold in the surface gas density regulating star formation, the star formation efficiency, the timescale for the formation of the thin disk, and the total surface mass density of the stellar halo. We use chemical evolution models that already have been tested on a large number of observational constraints. Methods. We test a model that considers a cosmological infall law. This law does not predict inside-out disk formation, but does allow the properties of the solar vicinity to be reproduced well. To check whether this model can reproduce the properties of the galactic disk, we study several cases. We lower the threshold of the surface gas density and assume that the star formation efficiency varies with radius. We test the same parameters in the two-infall model for the Galaxy. Finally, we complete some additional analyses of our simulations to test whether the cosmological infall law can account for the inside-out formation of the disk. Results. We find that to reproduce simultaneously the abundance, star formation rate and surface gas density gradients along the Galactic disk it is necessary to assume that inside-out disk formation occurs. The threshold of the gas density is unnecessary and a similar effect could be achieved by assuming a variable star formation efficiency. The derived new cosmological infall law contains a mild inside-out formation and is still unable to reproduce the disk properties. Conclusions. A cosmologically derived infall law with an inside-out process of disk formation and variable star formation efficiency can indeed reproduce well all the properties of the disk. However, the cosmological model presented here is of insufficient resolution to simulate accurately the inside-out formation for the disk. High resolution cosmological simulations should be performed to reproduce this behavior more accurately.